Integrative Multi-Omics Analysis Characterizes Immune Dysregulation and Altered CD4+ Central Memory T-Cell Abundance in Allergic Rhinitis

Background/Objectives: Allergic rhinitis (AR) is a highly prevalent chronic inflammatory disease of the upper airway characterized by immune dysregulation. This study aimed to systematically characterize the immunomodulatory landscape of AR and identify exploratory molecular and cellular features associated with disease-related immune remodeling. Methods: Public bulk transcriptomic datasets and single-cell RNA sequencing data were integrated to identify immunomodulatory-related differentially expressed genes (IMRDEGs), construct an immunomodulatory score (IM.Score), evaluate immune cell infiltration, and characterize cell-type composition and intercellular communication. Machine learning was used to derive an exploratory molecular signature, and L1000CDS2-based drug repositioning analysis was performed to identify in silico candidate compounds predicted to oppose AR-associated transcriptional signatures. Results: A total of 12 IMRDEGs were identified and used to construct the IM.Score, which was lower in AR samples relative to control samples. Immune infiltration analysis demonstrated that IM.Score stratification was associated with distinct immune microenvironmental profiles. Single-cell analysis revealed potential reductions in CD4+ central memory T cells, which represent an immune cellular alteration requiring further experimental verification, alongside attenuated intercellular communication involving this cell population. A six-gene exploratory molecular signature comprising NFKBIA, PDCD1, MYC, IFNG, FOXP3, and CD274 showed favorable performance in the training cohort (AUC = 0.992, 95% CI: 0.974–1.000) but failed to generalize in the external validation cohort (AUC = 0.500, 95% CI: 0.245–0.755), precluding clinical diagnostic interpretation at this stage. Drug repositioning analysis identified candidate compounds, including narciclasine and BRD-K91370081, with the potential to reverse AR-associated transcriptional alterations. Conclusions: This integrative multi-omics analysis identifies coordinated molecular, cellular, and communication-level immune alterations in AR. The IM.Score, altered CD4+ central memory T-cell abundance, and six-gene exploratory molecular signature may be regarded as hypothesis-generating candidate clues pending further experimental and clinical validation.